A fast distributed mining algorithm for association rules with item constraints
Chunhua Wang, Houkuan Huang, Honglian Li · 2002
Association rule mining is an important task of data mining. In practice, being often interested in a subset of association rules, users only want to get rules that contain a specific item. Integrating the item constraints into the mining process can acquire more efficient algorithms. This paper addresses the problem of distributed mining association rules with item constraints which are formalized Boolean expressions, and presents a fast algorithm called DMCA. Principles and implementation of the algorithm are discussed. Experiments prove efficiency of the algorithm.